A5084620092- Semantic Web and Ontologies
- Advanced Database Systems and Queries
- Logic, Reasoning, and Knowledge
- Multi-Agent Systems and Negotiation
- Data Management and Algorithms
- Service-Oriented Architecture and Web Services
- Algorithms and Data Compression
- Mobile Agent-Based Network Management
- Web Data Mining and Analysis
- Machine Learning in Bioinformatics
- Peer-to-Peer Network Technologies
- Complex Network Analysis Techniques
- Protein Structure and Dynamics
- Genomics and Phylogenetic Studies
- Advanced Neuroimaging Techniques and Applications
- Natural Language Processing Techniques
- Data Stream Mining Techniques
- Bayesian Modeling and Causal Inference
- Tensor decomposition and applications
- Data Mining Algorithms and Applications
- Recommender Systems and Techniques
- Data Quality and Management
- Enzyme Structure and Function
- Spam and Phishing Detection
- Topic Modeling
University of Calabria
2015-2024
University of Calabar
2007-2019
University of Reggio Calabria
2001-2004
Recent advances in image acquisition and processing techniques, along with the success of novel deep learning architectures, have given opportunity to develop innovative algorithms capable provide a better characterization neurological related diseases. In this work, we introduce neural network based approach classify Multiple Sclerosis (MS) patients into four clinical profiles. Starting from their structural connectivity information, obtained by diffusion tensor imaging represented as...
The task of an information integration system is to combine data residing at different sources, providing the user with a unified view them, called global schema. Users formulate queries over schema, and suitably answer user, who not obliged have any about sources. Recent developments in IT such as expansion Internet World Wide Web, made available users huge number generally autonomous, heterogeneous widely distributed: consequence, has emerged crucial issue many application domains, e.g.,...
The COVID-19 outbreak impacted almost all the aspects of ordinary life. In this context, social networks quickly started playing role a sounding board for content produced by people. Studying how dramatic events affect way people interact with each other and react to poorly known situations is recognized as relevant research task. Since automatically identifying country-based posts on generalized networks, like Twitter Facebook, difficult task, in work we concentrate Reddit megathreads,...
Abstract Detecting sets of relevant patterns from a given dataset is an important challenge in data mining. The relevance pattern, also called utility the literature, subjective measure and can be actually assessed very different points view. Rule-based languages like Answer Set Programming (ASP) seem well suited for specifying user-provided criteria to assess pattern form constraints; moreover, declarativity ASP allows easy switch between several order analyze In this paper, we make steps...
In recent years, the enormous development of Machine Learning, especially Deep has led to widespread adoption Artificial Intelligence (AI) systems in a large variety contexts. Many these provide excellent results but act as black-boxes. This can be accepted various contexts, there are others (e.g., medical ones) where result returned by system cannot without an explanation on how it was obtained. Explainable AI (XAI) is area well suited explain behavior that this paper, we propose...
Abstract This article considers the problem of reasoning on massive amounts (possibly distributed) data. Presently, existing proposals show some limitations: (i) quantity data that can be handled contemporarily is limited, because generally carried out in main-memory; (ii) interaction with external (and independent) Database Management Systems not trivial and, several cases, allowed at all; and (iii) efficiency present implementations still sufficient for their utilization complex tasks...
Abstract Consistent query answering over a database that violates primary key constraints is classical hard problem in research has been traditionally dealt with logic programming. However, the applicability of existing logic-based solutions restricted to data sets moderate size. This paper presents novel decomposition and pruning strategy reduces, polynomial time, computing consistent answer conjunctive subject collection smaller problems same sort can be solved independently. The new...
Social platforms are the preferred medium for many people to express their opinions on topics. This has led professionals from various fields (marketing, politics, research and development, etc.) demand increasingly advanced approaches capable of analyzing evolution user or community sentiments particular In this paper, we want make a contribution addressing issue. Specifically, propose model framework analyze dynamics in social platform. particular, our currently focuses three activities,...
In this paper, we propose an Extensible Markup Language (XML)-based multiagent recommender system for supporting online recruitment services. Our is characterized by the following features: 1) it handles user profiles personalizing job search over Internet; 2) based on intelligent agent technology; and 3) uses XML guaranteeing a light, versatile, standard mechanism information representation, storing, exchange. This paper discusses basic features of proposed system, presents results...